Data Annotation Guide – Definition, Techniques, Tools, Types and More
The quality of content – both text and visual – in your product descriptions determines online user experience, conversions, and sales. So, it is crucial to enrich your product catalogs with all relevant details and the right images to help purchase decisions.
Online retailers are locked in running battles over customers in an extremely competitive marketplace. They pamper customers with one-day deliveries, easy returns, instant refunds, jaw-dropping deals, and discounts to draw them in. However, all these efforts are wasted if the customer doesn’t get a positive shopping experience once on site.
Studies show the average cart abandonment ratio is 70%, of which 76% of consumers abandon products due to incomplete, inaccurate, misleading descriptions, and 66% do so due to poor product images.
To deliver superior customer experiences, e-commerce players need to enrich their online product catalogs with perfect textual and visual content (product descriptions, attributes, images, and videos). Doing this enhances product discovery with intelligent matching of the words and phrases that shoppers use to search for a product.
An eCommerce site can expect a nearly 35% increase in conversion rate through improved product descriptions, product attributes, and enticing product images. The combined eCommerce sales of the USA and EU are $738 billion. The potential of a 35% increase in conversions will translate to recovery of lost orders worth $260 billion merely through product data enrichment.
Communication overload on the customer care team
Erroneous, or insufficient product information in your eCommerce catalogs results in unnecessary workload, complaints, and help requests. This slows down response times, and leads to missed inquiries, and lost customers.
Higher cart abandonment rate
Shopping cart abandonment has been a persistent challenge for e-commerce players. Brands lose a staggering $18 billion in yearly sales revenue due to cart abandonment. These reasons include irrelevant product classification, confusing product information, and several others.
Higher product return rate
Research by McKinsey confirms that 25% of products purchased online are returned, especially fashion merchandise. This also adversely affects your logistics costs. $400 billion is the estimated cost of products returned to eCommerce players, according to the National Retail Federation.
Product returns happen mostly due to wrong expectations created by poor product tags, descriptions, and images. Shoppers expect products to match their descriptions. When that does not happen, they return the product, or leave bad reviews.
Loss of brand credibility
Losing trust in a specific e-commerce brand or player is a natural consequence of returning products, frequent cart abandonment, and customer service issues. Over 59% of shoppers trust such a retailer “slightly” or “not at all” for their next purchase. It’s disastrous for businesses that understand and prioritize customer lifetime value.
Product data enrichment is a series of steps through which 360-degree product-related information, including attributes, functions, dimensions, limitations, images, and others that customers or sellers may need, is put into the database against a product.
Enriched data helps deliver high performing product catalogs, placing all relevant information within easy reach of the customer.
How businesses perform product catalog classification and organize product attributes sets the stage for the customer experience. This depends on the careful curation of product information, such as descriptions, tags, categories, and other metadata.
Inevitably, a better customer experience translates into higher sales.
The Pareto principle fits best in this scenario. This means applying 20% effort into enriching your product data can result in 80% more sales.
Digitally connected consumers have grown smart of fake product reviews and tall claims. However, diligently maintained product catalogs ensure that you can win their trust.
As an e-commerce player, you know that relevant product suggestions help to upsell and cross-sell products. These increase the average order value. Here, proper product data enrichment saves you from the risk of incomplete or wrong product information.
For example, in cross-selling, you may want to pitch extra batteries to a customer who has purchased a DSLR camera. But you may have no updates on which battery will go with it and what the stock situation is. Similarly, for upselling, you may suggest a better version of a camera to a customer, but the attribute data may not support you. You can’t get an upsell.
Product data enrichment helps you overcome these challenges and allows customers to browse easily through alternatives and compare them.
Amazon does nothing different from what your eCommerce platform does. It ensures that product information is enriched regularly. It empowers them to host the “Compare with similar items” section for every product in stock.
Understock and overstock are two major pitfalls for online store owners when it comes to product catalog management. Inventory mismanagement has a deep and negative impact on overall business. Overstock leads to unnecessary capital investment, and understock leads to missing out on product sales. Only near-real-time data enrichment and the latest information on inventory situations can help you overcome these issues.
Today, e-commerce product enrichment specialists even go to the extent of providing solutions that display all your product metrics in one place. This enables you to make stocking decisions efficiently and in a timely manner.
With near-real-time information of your product stocks at your fingertips, you can mark which products sell the most, and which don’t. You can use these insights to provide better exposure to high-selling products. Knowledge of low-selling products will help you reduce exposure and stock less or decide on a new strategy.
Personalization is synonymous with product catalog management. Product data enrichment makes it possible for you to manage catalogs in a granular manner. You can set conditions in which product content is displayed according to individual customer preferences. This is now an established online retail strategy.
Sales counters don’t start ringing if your inventory data is outdated, and customers are misinformed. Regular and consistent product data enrichment for catalogs removes the risk of putting wrong stock information before customers.
Aesthetic and relevant product information raises the chances of online store purchases. To a great extent, it depends on high-performing product catalogs. Product data enrichment makes this possible. Better product catalogs offer a holistic purchasing experience. Comprehensive product data and descriptions help the customer make a faster buy and reinforce purchase decisions, reducing the chances of returns and the purchaser’s regret.
Successful sales happen only when catalogs have accurate product descriptions, dynamic page elements, and complementary and alternative product listings. There must also be proper categorization and tagging of catalog items. All these, and high sales, depend on the accuracy and depth of the data enrichment.
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